On top of that, business entities are heavily interconnected, with hierarchical, variable and sparse
relations: when cross‑cutting views are required, the overall data model grows quickly more akin to a
complex graph than to a bare table.

no quick way to integrate data silos to capture value from interconnections

The Solution Knowledge graphs leverage linked data, graph databases, natural
language processing and machine learning to weave fragmented, unstructured and disorganised data
into a hyperlinked read/write data hub easily available to people and applications, with no impact
on existing processes and systems.

Knowledge graphs are easily implemented with an agile and incremental approach, delivering value over
short working cycles, with low risk and limited investment; they also rationalize and factor
previously uncoordinated data extraction and integration activities, cutting duplicated efforts and
related security risks.

We provide end‑to‑end support in the implementation of turnkey solutions
based on enterprise knowledge graphs through our professional and development
services and our open-source linked data
platform.